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Indiana University Bloomington

PwC Faculty Fellow

Error vs. Irregularity Classification of GAO Restatement Data

This dataset contains all US Government Accountability Office (GAO) restatements classified as errors versus irregularities using the methodology outlined in Hennes, Leone, and Miller (2008).

Please note that this posted dataset is not the same as the sample used in Hennes, Leone, and Miller (2008). We did not use the 2002-2006 sample in our study, because it was not available when we started our project. However, the methodology used to distinguish errors from irregularities is identical.

This dataset is freely available. We only request that if you use a data you reference our paper and acknowledge the data source.


References:
Hennes, K., A. Leone, and B. Miller. (2008). The Importance of Distinguishing Errors from Irregularities in Restatement Research: The Case of Restatements and CEO/CFO The Accounting Review. 83 (6): 1487-1519.

Error vs. Irregularity Classification of GAO Restatement Dataset